Пример #1
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def enhanceImage(algorithm, image, enhanceSteps):
	kernel = np.array([1 << idx for idx in range(9)]).reshape(3, 3)
	imageFromAlgorithmIndices = np.vectorize(cache(lambda idx: algorithm[idx]))

	fillValue = 0
	for _ in range(enhanceSteps):
		algorithmIndices = convolve2d(image, kernel, fillvalue=fillValue)
		image = imageFromAlgorithmIndices(algorithmIndices)
		fillValue = algorithm[(0, -1)[fillValue]]

	return image
Пример #2
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    def __init__(self, tree, updater, is_scene_update):
        """:tree: tree which should be updated
        :_updater: generator which should update given tree
        :is_exhausted: the status of the generator - read only
        :last_node: last node which going to be processed by the generator
        - read only"""
        self.tree: SvTree = tree
        self.is_scene_update: bool = is_scene_update
        self.is_exhausted = False
        self.last_node = None

        self._updater: Generator = updater
        self.__hash__ = cache(self.__hash__)
Пример #3
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    def decorator(user_function: F) -> F:
        """The decorator focus on given condition."""
        cache_decorated_function = cast(F, cache(user_function))

        @wraps(user_function)
        def decorated(*args: Any, **kwargs: Any) -> Any:
            """The decorated user function."""
            if not condition(user_function, args, kwargs):
                # Execute directly.
                return user_function(*args, **kwargs)
            return cache_decorated_function(*args, **kwargs)

        return cast(F, decorated)
Пример #4
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def test():
    """Simple test program."""
    import sys
    url = "http://www.python.org/"
    if sys.argv[1:]: url = sys.argv[1]
    c = cache()
    for i in range(3):
        api = c.open(url, 'GET', {})
        while 1:
            message, ready = api.pollmeta()
            print(message)
            if ready:
                meta = api.getmeta()
                print(repr(meta))
                break
        while 1:
            message, ready = api.polldata()
            print(message)
            if ready:
                data = api.getdata(512)
                print(repr(data))
                if not data:
                    break
        api.close()
Пример #5
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def _singleton_fixture(f):
    return _fixture(cache(f))
Пример #6
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import arbor
import functools
from functools import lru_cache as cache
import unittest
from pathlib import Path
import subprocess
import warnings
import atexit

_mpi_enabled = arbor.__config__["mpi"]
_mpi4py_enabled = arbor.__config__["mpi4py"]

# The API of `functools`'s caches went through a bunch of breaking changes from
# 3.6 to 3.9. Patch them up in a local `cache` function.
try:
    cache(lambda: None)
except TypeError:
    # If `lru_cache` does not accept user functions as first arg, it expects
    # the max cache size as first arg, we pass None to produce a cache decorator
    # without max size.
    cache = cache(None)


def _fix(param_name, fixture, func):
    """
    Decorates `func` to inject the `fixture` callable result as `param_name`.
    """
    @functools.wraps(func)
    def wrapper(*args, **kwargs):
        kwargs[param_name] = fixture()
        return func(*args, **kwargs)
Пример #7
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# modify it under the terms of the MIT License; see the
# LICENSE file for more details.

import functools

from flask import current_app, request
from flask_multipass import InvalidCredentials, Multipass, NoSuchUser
from werkzeug.local import LocalProxy

from indico.core.config import config
from indico.core.limiter import make_rate_limiter
from indico.core.logger import Logger

logger = Logger.get('auth')
login_rate_limiter = LocalProxy(
    functools.cache(
        lambda: make_rate_limiter('login', config.FAILED_LOGIN_RATE_LIMIT)))


class IndicoMultipass(Multipass):
    @property
    def default_local_auth_provider(self):
        """The default form-based auth provider."""
        return next((p for p in self.auth_providers.values()
                     if not p.is_external and p.settings.get('default')), None)

    @property
    def sync_provider(self):
        """The synchronization provider.

        This is the identity provider used to sync user data.
        """
Пример #8
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def single_thread_with_cache(inputs):
    """
    Compute single threaded with cache.
    """
    f_memoized = cache(f)
    return [f_memoized(x) for x in inputs]
Пример #9
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    """
    objects = values_from_signal(signal_response, return_plugins=True)
    if plugin_attr is not None:
        for plugin, cls in objects:
            setattr(cls, plugin_attr, plugin)
    mapping = {getattr(cls, name_attr): cls for _, cls in objects}
    # check for two different objects having the same name, e.g. because of
    # two plugins using a too generic name for their object
    conflicting = {cls for _, cls in objects} - set(mapping.values())
    if conflicting:
        names = ', '.join(sorted(getattr(x, name_attr) for x in conflicting))
        raise RuntimeError(f'Non-unique object names: {names}')
    return mapping


_inspect_signature = functools.cache(inspect.signature)


def make_interceptable(func, key=None, ctx=None):
    """Create a wrapper to make a function call interceptable.

    The returned wrapper behaves like the original function, but it triggers a signal
    which can modify its call arguments or even override the return value (in which
    case the original function would not get called at all, unless the signal handler
    decides to do so itself).

    This function can also be used as a decorator; in that case neither a key nor context
    can be provided (but it would not make sense anyway).

    :param func: The function to make interceptable
    :param key: An optional key in case using just the function name would be too generic
    if j is None: j = len(y)
    if i == 0: return j
    if j == 0: return i
    return min(
        edit_dist(x, y, i - 1, j - 1) + (x[i - 1] != y[j - 1]),
        edit_dist(x, y, i, j - 1) + 1,
        edit_dist(x, y, i - 1, j) + 1,
    )


print(f"Recursive edit_dist({x},{y}) = {edit_dist(x, y)}")

# Memoisation as if we had used the decorator (explicitly using
# cache() works the same way).
from functools import cache
edit_dist = cache(edit_dist)

print(f"Cached edit_dist({x},{y}) = {edit_dist(x, y)}")


def edit_dist(x, y, i=None, j=None, tbl=None):
    if i is None: i = len(x)
    if j is None: j = len(y)
    if tbl is None: tbl = {}

    if i == 0:
        tbl[i, j] = j
    elif j == 0:
        tbl[i, j] = i
    else:
        tbl[i, j] = min(
Пример #11
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 def update_event(self, inp=-1):
     self.set_output_val(0, functools.cache(self.input(0)))
Пример #12
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 def cache_e(expression):
     return cache(e(expression))
Пример #13
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 def __init__(self, load_fn: Callable[[], Awaitable[Sequence[ItemType]]]):
     self.load_fn = functools.cache(load_fn)
Пример #14
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 def cached_property(f):
     cf = functools.cache(f)
     return property(cf)
Пример #15
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from indico.modules.rb.models.rooms import Room
from indico.modules.users.util import get_user_by_email


try:
    import cx_Oracle
except ImportError:
    cx_Oracle = None


class SkipRoom(Exception):
    pass


# memoize results in case we are on the slower auth API
get_user_by_email = functools.cache(get_user_by_email)


def OutputTypeHandler(cursor, name, defaultType, size, precision, scale):
    """
    Unicode output handler for oracle connections
    Source: http://www.oracle.com/technetwork/articles/dsl/tuininga-cx-oracle-084866.html
    """
    if defaultType in (cx_Oracle.STRING, cx_Oracle.FIXED_CHAR):
        return cursor.var(str, size, cursor.arraysize)


def _get_room_role_map(connection, logger):
    roles = defaultdict(set)
    cursor = connection.cursor()
    cursor.execute('SELECT BUILDING, FLOOR, ROOM_NUMBER, EMAIL FROM aispub.app_indico_space_managers')
Пример #16
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 def method(self, *args, **kwargs):
     instance_cache = cache_dict.get(self)
     if instance_cache is None:
         instance_cache = cache(partial(func, self))
         cache_dict[self] = instance_cache
     return instance_cache(*args, **kwargs)